The Centrality of Economics in Teaching Economic Statistics - Cain, Glen G. (American Economic Review, 1987)
The elementary course in economic statistics must devote more time to statistics than to economics. Students who major in economics will take at least six courses in economics, but the course in economic statistics may be their only course in statistics. Nevertheless, the basic purposes of economics should be kept in mind in shaping the course. Although the statistical methods used in applied economics deal with measurable variables, it is my view that the ultimate purpose of economics as an applied social science is the improvement of human welfare, which is intrinsically an unmeasurable concept. Our recognition of the unattainable ideal does not stop us from obtaining less than ideal measurements that are nevertheless useful. The two basic problems in this task of economic measurement are (a) to define and measure the correct outcomes, and (b) to measure their determinants so that we can predict and, ideally, influence the outcomes. The contribution that the science of statistics can make to these tasks is fundamentally that of the art and craft of using observed sample data to make inferences about unknown population parameters in economics. Inferential statistics is fundamental. Descriptive statistics, which is the art and craft of organizing and summarizing sample data, is useful and necessary for learning inferential statistics, but it is not fundamental in its own terms. Turning to the structure of the course in economic statistics, let us apply a principle of economics to its teaching by specifying the constraints under which we seek to optimize our goals. Four major constraints face the teacher of elementary economic statistics: 1) the limited time in a one-semester course; 2) the typically large size and heterogeneity of the class; 3) the limited economic and, especially, mathematical background of most of the students; and 4) the limited skills of the teacher. A word about constraint 4, which implicitly qualifies much of what follows. Instructors of economic statistics have varying talents for and preferences about the course, and it is appropriate to play to one's strengths. If someone is a whiz at teaching probability, this topic by this instructor may captivate students and inspire them toward an understanding of inferential statistics. Another instructor may be skillful in using examples from such economic topics as income distribution or macroeconomics to illustrate how economists use sample evidence to estimate and test interesting relationships between outcome variables and their determinants. We each have our own styles of teaching, and my suggestions for content and methods should be viewed as subservient to any particular instructor's tastes and skills. With that qualification, I turn next to the content of the course.